Telethon Institute of Genetics and Medicine (TIGEM), Naples 80131, Italy.
Chaos. 2013 Jun;23(2):025106. doi: 10.1063/1.4808247.
We describe an innovative experimental approach, and a proof of principle investigation, for the application of System Identification techniques to derive quantitative dynamical models of transcriptional regulation in living cells. Specifically, we constructed an experimental platform for System Identification based on a microfluidic device, a time-lapse microscope, and a set of automated syringes all controlled by a computer. The platform allows delivering a time-varying concentration of any molecule of interest to the cells trapped in the microfluidics device (input) and real-time monitoring of a fluorescent reporter protein (output) at a high sampling rate. We tested this platform on the GAL1 promoter in the yeast Saccharomyces cerevisiae driving expression of a green fluorescent protein (Gfp) fused to the GAL1 gene. We demonstrated that the System Identification platform enables accurate measurements of the input (sugars concentrations in the medium) and output (Gfp fluorescence intensity) signals, thus making it possible to apply System Identification techniques to obtain a quantitative dynamical model of the promoter. We explored and compared linear and nonlinear model structures in order to select the most appropriate to derive a quantitative model of the promoter dynamics. Our platform can be used to quickly obtain quantitative models of eukaryotic promoters, currently a complex and time-consuming process.
我们描述了一种创新的实验方法和原理验证研究，用于将系统辨识技术应用于从活细胞中的转录调控中推导出定量动态模型。具体来说，我们构建了一个基于微流控设备、延时显微镜和一组自动化注射器的系统辨识实验平台，所有这些都由计算机控制。该平台允许将任何感兴趣的分子的时变浓度递送到微流控设备中捕获的细胞（输入）中，并以高采样率实时监测荧光报告蛋白（输出）。我们在酵母酿酒酵母中的 GAL1 启动子上测试了该平台，该启动子驱动与 GAL1 基因融合的绿色荧光蛋白（Gfp）的表达。我们证明了系统辨识平台能够准确测量输入（培养基中的糖浓度）和输出（Gfp 荧光强度）信号，从而可以应用系统辨识技术来获得启动子的定量动力学模型。我们探索并比较了线性和非线性模型结构，以选择最适合推导启动子动力学定量模型的结构。我们的平台可用于快速获得真核启动子的定量模型，目前这是一个复杂且耗时的过程。
